5 ms·
This is an example of what is making ML so hard for uninitiated. 160 characters per line, avoidance of using spaces, abbreviations everywhere which are not exp
by timeattack 7y ago
This is an example of what is making ML so hard for uninitiated.
160 characters per line, avoidance of using spaces, abbreviations everywhere which are not explained anywhere, lack of autoformatter.
This looks like a recipe for write-only code for me.
My pet theory is that people which invent such styles are actually not a apt touchtypers, so they avoid typing many characters because it's kind of pain for them.
- raducu 7y agoIf the abbreviations are standard across the domain space, they are fine imho. But as far as I remember from Jeremy's videos, that was indeed not the case.
- timeattack 7y agoI can agree if there are not so many abbreviations, but when almost every single line is full of them, that is what makes code incomprehensible.
- hivacruz 7y agoI love FastAI videos. I learned DL/ML thanks to their courses. But yes, sometimes in their videos, when Jeremy was showing FastAI code or a bunch of lines in a Jupyter Notebook, all these one-liners were hard to understand. You are already trying to learn a field that you know nothing about and you have to try to understand at the same the code which is written in a "weird" way. Every time I opened their notebooks, I automatically reformatted their code.